IB Digital Society 3.6D Evolution of AI Key Definitions

A period when interest and funding in artificial intelligence collapse after inflated promises fail to materialise. AI has gone through several such winters followed by renewed booms.

A hypothetical AI that could understand, learn, and apply knowledge across any task as flexibly as a human. Also called strong or full AI, it does not yet exist.

A field of computer science dedicated to building systems that can replicate human intelligence and answer complex queries.

The mid-twentieth-century study of control and communication in animals and machines, especially feedback loops. It helped lay the groundwork for artificial intelligence by treating thinking as information processing.

A form of machine learning that uses artificial neural networks with many layers to learn complex patterns directly from large amounts of raw data, powering tasks such as image and speech recognition.

The observation, made by Gordon Moore in 1965, that the number of transistors on a chip roughly doubles about every two years, driving rapid growth in computing power.

A speculative AI that would surpass human intelligence across virtually every field. It remains hypothetical and is central to debates about the long-term risks and future of AI.

A hypothetical future point at which AI becomes able to improve itself so rapidly that technological change accelerates beyond human control or understanding. It is speculative and heavily debated.